Online Response Time Research Articles

A new lattice-based online/offline signatures framework for low-power devices

Lattice-based online/offline signature scheme enjoys the advantage of resisting quantum feature besides the short online response time. The existing Fiat-Shamir with aborts paradigm candidates do not have perfect online/offline property, and the hash-sign-switch ones usually increase the signature sizes. In this paper we mainly address its online time and the length of signature issues, and propose a new and efficient paradigm of its construction for lattice assumptions over rings. In this paradigm the signer tries to sign for a random string and the message respectively. Specifically, we first discuss the generic construction of Fiat-Shamir lattice-based signatures. Then for a large class of lattice-based relations over rings, we propose an improved framework designed for low-power devices. This new framework allows the signer to extract a part of the signature only for a random string chosen in offline time, and thus can obtain the whole signature by less online time. In addition, the resulting scheme slightly reduces the signature size compared to the Fiat-Shamir counterparts. The performance analysis shows that our construction is efficient.

Impact of social cognitive propensity on the processing of nontransparent sentential meaning

This study investigates the influence of individual social-cognitive propensity in the processing of nontransparent sentential meaning, exemplified by the morpho-syntactically unsupported iterative meaning in “The frog hopped for five minutes.” Results of our speeded questionnaire in Mandarin Chinese showed that social cognitive propensity of typically-developed individuals, indexed by autistic-like traits, significantly correlated with online response times (RTs) of naturalness rating, while the effect was absent in offline rating scores. Individuals with higher autistic-like traits (i.e., lower social skills) took longer to process sentences with nontransparent meaning for making judgments. We argue that the computation of these sentences involves meaning contextualization—construing a coherent conceptual representation by integrating multiple lexical representations and evaluating sentential-discourse context. Such context-dependent meaning processing requires sufficient context sensitivity, which varies across individuals in association with social cognitive propensity. The pattern is captured by the Dual-Process Approach to information processing and social cognition: individuals with higher autistic-like traits are prone to deliberative reasoning with lower contextual sensitivity. This cognitive bias leads to greater cost when the full comprehension demands meaning contextualization, and therefore longer RTs in evaluating appropriate interpretations. The findings show that individual variability in social cognitive propensity modulates the online computation of nontransparent sentential meaning.

Quasi-static scheduling based error recovery for Digital microfluidic biochips

Digital microfluidic biochips (DMFBs) are designed as an alternative to traditional laboratories for bio-chemical synthesis. DMFBs are a class of lab-on-a-chip devices. Error recovery of transient faults which are fluidic-level operations is critical for accuracy sensitive applications like clinical diagnostics and drug discovery. If the errors are not detected and corrected as soon as their occurrence, they propagate till the end of assay and entire assay has to be re-executed for error correction. In this work, we propose a quasi-static scheduling based error recovery (QSSER) for DMFBs. The proposed method can work with both sensor-based and CCD camera-based systems, which are used to detect errors. The proposed QSSER scheduler constitutes offline and online components. Quasi-static scheduling determines offline a set of fault-tolerant schedules for different faults/errors that might occur and decides online which schedule is correct to follow out of offline computed schedules for particular error scenarios. QSSER reduces the online response time and assay completion times while tolerating the maximum transient faults.

P650 IBD care from the patient perspective: The patient’s turn

Abstract Background There is an increased focus on patient reported outcomes and patient reported experiences as means to optimize provided care. Both are considered essential in improving quality and service. Zuyderland Medical Centre (ZMC) is transforming its inflammatory bowel disease (IBD) care into a patient oriented IBD Centre (PGC IBD) as a way to provide modern patient centred care. The project ‘Patient aan zet’ is an initiative of Crohn & Colitis NL (CCNL) and takes place in several hospitals. The aim of the project is to optimize quality of care for adult patients with IBD by ensuring that the patient is properly and unambiguously informed and the patients involvement increases in treatment. Methods A cross-sectional survey using a questionnaire was performed to map out expectations and experiences of patients with the IBD outpatient clinic of ZMC. This questionnaire (part of the project ‘Patient aan zet’) was developed by CCNL as an online self-completion instrument. The results of this questionnaire were assessed in a subsequent discussion group. All IBD-patients presenting for an outpatient appointment at ZMC in March 2021, received an e-mail with a link to the questionnaire. In total, 500 e-mails were sent. After completing the questionnaire, patients were given the opportunity to sign up for a discussion group. Results In total, 198 participants completed the questionnaire fully or partially (40%) (Table 1). We found patients were satisfied with health care in general and with the information supply concerning IBD specifically. Use of the online monitoring tool MyIBDCoach and response time in the online monitoring tool contributed to positive judgment. In the discussion group emerged that continued attention must be paid to the impact of endoscopic procedures from the patient perspective as endoscopic procedures (as part of the mucosal healing concept) may induce lasting and major impact on patients disease experience. In line with the ongoing corona pandemic developments, patient prefer a combination of check-up appointments by phone and at the outpatient clinic depending on (burden of) disease activity. Finally, specific attention is necessary for patients with a longstanding disease history. Needs concerning dietary advice and psychosocial support appear to vary over time. Conclusion ZMC is transforming its IBD care into a PGC IBD as a way to provide optimal and patient centred care. Involving patient in this process has given direction to optimizing patient information and patient involvement. The experiences gained from this process will be used to evaluate the PGC IBD after implementation and, together with the patient association, to develop a PREM that can be used to optimize IBD care.

Metric hull as similarity-aware operator for representing unstructured data

• We propose the novel concept of metric hulls. • We define the covered operator using mutual distances only. • We evaluate the proposal on synthetic and real-life data. • Our method achieves online response times. • We show that a few hull objects provide high coverage in comparison to the related work. Similarity searching has become widely utilized in many online services processing unstructured and complex data, e.g., Google Images. Metric spaces are often applied to model and organize such data by their mutual similarity. As top-k queries provide only a local view on data, a data analyst must pose multiple requests to observe the entire dataset. Thus, group-by operators for metric data have been proposed. These operators identify groups by respecting a given similarity constraint and produce a set of objects per group. The analyst can then tediously browse these sets directly, but representative members may provide better insight. In this paper, we focus on concise representations of metric datasets. We propose a novel concept of a metric hull which encompasses a given set by selecting a few objects. Testing an object to be part of the set is then made much faster. We verify this concept on synthetic Euclidean data and real-life image and text datasets and show its effectiveness and scalability. The metric hulls provide much faster and more compact representations when compared with commonly used ball representations.

A New and Efficient Lattice-Based Online/Offline Signature From Perspective of Abort

Abstract Lattice-based online/offline signature is attractive for the merit of resisting quantum attacks besides the short online response time. Prior to this work, the hash-sign-switch paradigm lattice-based online/offline signatures usually increase the length of each signature, and the Fiat–Shamir candidates are highly inefficient due to multiple aborts in online signing phase. In this work we mainly address its efficient issue and propose a new paradigm of its construction in the perspective of abort. In this paradigm, one tries to remove one or more aborts from online to offline signing phase by $\Gamma $-transformation. Specifically, this work proposes an efficient lattice-based online/offline signature scheme with fewer online aborts and thus allows the signer to obtain a valid signature by fewer online repetitions. Through this way, the resulting scheme can reduce much online signing time with the same signature size. The performance evaluation shows that our scheme is efficient and practical.

Highly accurate particulate matter detection assisted by an air heater based on a silver nanowire film

Recently, many studies have been carried out to solve the particulate matter pollution problem. However, the detection accuracy for particulate matter in the atmosphere remains unsatisfactory due to the influence of the air relative humidity. Herein, we report a Ag nanowire film air heater to enhance the detection accuracy through internal heating. From air temperature and air relative humidity relationship analysis, it has been found that the Ag nanowire film air heater can form the most suitable air relative humidity in the detection system, thereby enhancing the detection accuracy. Consequently, the Ag nanowire film air heater-assisted light scattering particulate matter detector has achieved tremendous enhancement in its detection accuracy, which is comparable with the data obtained by the beta gauge method. Film resistance plays a key role in internal air temperature distribution and the resultant air relative humidity at given voltages. To achieve the most suitable air relative humidity for continuous online monitoring, response time and power consumption should be balanced. Therefore, guidance for designing Ag nanowire films with proper resistance used in an optional-sized detector has been given for quick response, high accuracy and low power consumption. This work is of significance for providing insight for future studies in particulate matter detection and pollution remediation.

Cost Optimization for the Coupled Video Delivery Networks

Video delivery networks (VDNs) are one of the key enablers for alleviating contradiction between demands increasing for online video and response time of users accessing video content. However, existed works mainly adopt either proactive or reactive delivery scheme, which leads to the problems of backbone traffic overloaded and delays increased. In these works, the impact of performance indicators, such as bandwidth, delay, and personalized demand on delivery cost are not comprehensively taken into account. To overcome these problems, we propose a cost optimization for coupled video delivery model (CO-CVDM), which combines coupled proactive delivery and coupled reactive delivery method to minimize delivery cost in terms of bandwidth consumption, delay performance, personalized demand and construct a multicast delivery tree for the video delivery. The coupled delivery cost minimization problem under constraint conditions is formulated. Since this problem is NP-hard and is prohibitively difficult to solve, we develop a heuristic multicast delivery tree (HMDT) algorithm to provide more optimized approximate cost. Based on this, we extend CO-CVDM to distribute video in a dynamic scenario. Specifically, with dynamic change of user's requirement for video, the process of video delivery is truncated into a sequence of static graphs and the change of interest attenuation is modeled with human forgetting curve. Finally, the numerical simulations are conducted to validate the advantage of CO-CVDM in terms of optimization delivery cost, and the delivery cost is inversely proportional to the attenuation of user interest.

Auditory statistical learning in children: Novel insights from an online measure

AbstractNonadjacent dependency learning is thought to be a fundamental skill for syntax acquisition and often assessed via an offline grammaticality judgment measure. Asking judgments of children is problematic, and an offline task is suboptimal as it reflects only the outcome of the learning process, disregarding information on the learning trajectory. Therefore, and following up on recent methodological advancements in the online measurement of nonadjacent dependency learning in adults, the current study investigates if the recording of response times can be used to establish nonadjacent dependency learning in children. Forty-six children (mean age: 7.3 years) participated in a child-friendly adaptation of a nonadjacent dependency learning experiment (López-Barroso, Cucurell, Rodríguez-Fornells, & de Diego-Balaguer, 2016). They were exposed to an artificial language containing items with and without nonadjacent dependencies while their response times (online measure) were measured. After exposure, grammaticality judgments (offline measure) were collected. The results show that children are sensitive to nonadjacent dependencies, when using the online measure (the results of our offline measure did not provide evidence of learning). We therefore conclude that future studies can use online response time measures (perhaps in addition to the offline grammaticality judgments) to further investigate nonadjacent dependency learning in children.

Linguistic relativity in L2 acquisition

Abstract Proponents of the Linguistic Relativity Principle has maintained that the language we use modulates our thinking and that our thinking also shapes or determines how the language is parsed and understood. Existing research has provided compelling evidence for the above relativistic view in monolingual speakers. Recently, a growing number of studies have also started to investigate the relativistic view on language and thought in L2 learners. These L2 studies have yielded evidence regarding the cognitive constraint of an early-learned language (e.g. L1) on the later-learned language (e.g. L2). Despite this vigorous research effort, much remains unknown about whether the cognitive development in the later-learned language would modulate how the early-learned language is parsed (lower-level processing) and understood (higher-level processing). To fill the gap, this study drew on the self-paced reading experimental paradigm to study linguistic relativity effects on advanced L2 learners’ reading of L1 (Chinese) counterfactual statements – a concept encoded differently in these learners’ L1 and L2. The participants’ online response time and offline accuracy data were both the foci of the analyses; while the analyses of the response time data were suggestive of the participants’ initial lower-level parsing of the L1 counterfactual statements, the analyses of the accuracy data shed light on how the concept of counterfactuality is represented and understood in the L1. Throughout these analyses, this study intends to address the following questions: Does L2 acquisition impose any cognitive constraint on bilinguals’ lower-level L1 parsing and/or on their higher-level L1 processing? If so, in what way and to what extent? Furthermore, the study also intends to empirically establish whether the cognitive constraint as stipulated by the Linguistic Relativity Principle would be modulated by different onset age of learning the L2 (early vs. late). Findings of this study are discussed vis-à-vis the Linguistic Relativity Principle, L2 processing mechanism, and L2 literacy instruction.

EHealth Literacy: Patient Engagement in Identifying Strategies to Encourage Use of Patient Portals Among Older Adults.

Innovations in chronic disease management are growing rapidly as advancements in technology broaden the scope of tools. Older adults are less likely to be willing or able to use patient portals or smartphone apps for health-related tasks. The authors conducted a cross-sectional survey of older adults (ages ≥50) with hypertension or diabetes to examine relationships between portal usage, interest in health-tracking tools, and eHealth literacy, and to solicit practical solutions to encourage technology adoption. Among 247 patients surveyed in a large integrated delivery health system between August 2015 and January 2016, eHealth literacy was positively associated with portal usage (OR [95% CI]: 1.3 [1.2-1.5]) and interest in health-tracking tools (1.2 [1.1-1.3]). Portal users compared to nonusers (N = 137 vs.110) had higher rates of interest in using websites/smartphone apps to track blood pressure (55% vs. 36%), weight (53% vs. 35%), exercise (53% vs. 32%), or medication (46% vs 33%, all P < 0.05). Portal users noted cumbersome processes for accessing portals and variations in provider availability for online scheduling and response times to messages. Portal nonusers expressed concerns about data security, lack of personalization, and limited perceived value of using portals. Both groups noted the importance of computer literacy and technical support. Patient stakeholders recommended marketing initiatives that capture patient stories demonstrating real-life applications of what patients can do with digital technology, how to use it, and why it may be useful. Health systems also must screen for eHealth literacy, provide training, promote proxy users, and institute quality assurance that ensures patients' experiences will not vary across the system.

Real-time topic-aware influence maximization using preprocessing.

BackgroundInfluence maximization is the task of finding a set of seed nodes in a social network such that the influence spread of these seed nodes based on certain influence diffusion model is maximized. Topic-aware influence diffusion models have been recently proposed to address the issue that influence between a pair of users are often topic-dependent and information, ideas, innovations etc. being propagated in networks are typically mixtures of topics.MethodsIn this paper, we focus on the topic-aware influence maximization task. In particular, we study preprocessing methods to avoid redoing influence maximization for each mixture from scratch.ResultsWe explore two preprocessing algorithms with theoretical justifications.ConclusionsOur empirical results on data obtained in a couple of existing studies demonstrate that one of our algorithms stands out as a strong candidate providing microsecond online response time and competitive influence spread, with reasonable preprocessing effort.Electronic supplementary materialThe online version of this article (doi:10.1186/s40649-016-0033-z) contains supplementary material, which is available to authorized users.

스마트폰 응용 프로그램의 사용자 경험 향상을 위한 사용자 중심 반응 시간 분석 도구

We propose a novel user-perceived performance optimization framework for the Android platform that takes advantage of the user-centric response time analysis. To this end, we propose a new definition of response time, which we call the user-centric response time, as a metric for the quality of user-perceived performance of the smartphone application. In this paper, we describe the design and implementation of an on-line user-centric response time analyzer for Android-based smartphones, which provides smartphone application developers with valuable insight for user-perceived performance optimization. We implemented the user-centric response time analyzer on the Android platform, version 4.0.4 (ICS) running on a Galaxy Nexus smartphone. From our experimental results, the proposed user-centric response time analyzer accurately estimates user-centric response times with an accuracy of 92.0% compared to manually measured times with less than 1% performance penalty. In order to evaluate the efficiency of the proposed framework, we were able to reduce the user-centric response time of the target application by up to 16.4% based on the evaluation results by the proposed framework.

Comparison of functional network connectivity for passive-listening and active-response narrative comprehension in adolescents.

Comprehension of narrative stories plays an important role in the development of language skills. In this study, we compared brain activity elicited by a passive-listening version and an active-response (AR) version of a narrative comprehension task by using independent component (IC) analysis on functional magnetic resonance imaging data from 21 adolescents (ages 14-18 years). Furthermore, we explored differences in functional network connectivity engaged by two versions of the task and investigated the relationship between the online response time and the strength of connectivity between each pair of ICs. Despite similar brain region involvements in auditory, temporoparietal, and frontoparietal language networks for both versions, the AR version engages some additional network elements including the left dorsolateral prefrontal, anterior cingulate, and sensorimotor networks. These additional involvements are likely associated with working memory and maintenance of attention, which can be attributed to the differences in cognitive strategic aspects of the two versions. We found significant positive correlation between the online response time and the strength of connectivity between an IC in left inferior frontal region and an IC in sensorimotor region. An explanation for this finding is that longer reaction time indicates stronger connection between the frontal and sensorimotor networks caused by increased activation in adolescents who require more effort to complete the task.

A similarity-based approach for data stream classification

Incremental learning techniques have been used extensively to address the data stream classification problem. The most important issue is to maintain a balance between accuracy and efficiency, i.e., the algorithm should provide good classification performance with a reasonable time response. This work introduces a new technique, named Similarity-based Data Stream Classifier (SimC), which achieves good performance by introducing a novel insertion/removal policy that adapts quickly to the data tendency and maintains a representative, small set of examples and estimators that guarantees good classification rates. The methodology is also able to detect novel classes/labels, during the running phase, and to remove useless ones that do not add any value to the classification process. Statistical tests were used to evaluate the model performance, from two points of view: efficacy (classification rate) and efficiency (online response time). Five well-known techniques and sixteen data streams were compared, using the Friedman’s test. Also, to find out which schemes were significantly different, the Nemenyi’s, Holm’s and Shaffer’s tests were considered. The results show that SimC is very competitive in terms of (absolute and streaming) accuracy, and classification/updating time, in comparison to several of the most popular methods in the literature.

BLAST-SSAHA Hybridization for Credit Card Fraud Detection

A phenomenal growth in the number of credit card transactions, especially for online purchases, has recently led to a substantial rise in fraudulent activities. Implementation of efficient fraud detection systems has thus become imperative for all credit card issuing banks to minimize their losses. In real life, fraudulent transactions are interspersed with genuine transactions and simple pattern matching is not often sufficient to detect them accurately. Thus, there is a need for combining both anomaly detection as well as misuse detection techniques. In this paper, we propose to use two-stage sequence alignment in which a profile analyzer (PA) first determines the similarity of an incoming sequence of transactions on a given credit card with the genuine cardholder's past spending sequences. The unusual transactions traced by the profile analyzer are next passed on to a deviation analyzer (DA) for possible alignment with past fraudulent behavior. The final decision about the nature of a transaction is taken on the basis of the observations by these two analyzers. In order to achieve online response time for both PA and DA, we suggest a new approach for combining two sequence alignment algorithms BLAST and SSAHA.

Dealing efficiently with data-center disasters

In disaster-resilient systems, wide-area networks play the dual roles of solution and problem. They allow systems to survive disasters because different parts of a system can be located in geographically dispersed locations. They present a problem since communication of disaster-recovery information along wide-area links has high latency. The challenge is to continuously send disaster-recovery information to backup data centers without seriously degrading the on-line response time of the primary data center. We present a disaster-resilient, atomic broadcast algorithm that meets this challenge. One key to achieving disaster resilience at a reasonable cost is to define an atomic broadcast abstraction that is tailored to the multi-data-center setting. Unlike traditional atomic broadcast abstractions, our hierarchical atomic broadcast (HABcast) abstraction gives different delivery guarantees to processes in different data centers. The HABcast properties reflect the fact that only the processes in the primary data center are online (i.e., connected to clients). Roughly speaking, because processes in a backup data center do not interact with external entities, we can give them weaker delivery guarantees without compromising the overall reliability of the system. Another key to practical disaster resilience is for algorithms to exploit the underlying fail-over mechanism between data centers. The fail-over to a backup data center is initiated by human operators, so-called “push-button” switch-over. Because the fail-over decision is made by a human operator, the system itself does not have to guard against false disaster suspicions, and can thus be more efficient. Our HABcast algorithm exploits the above aspects of disaster-resilient systems. Basically, the algorithm overlays a primary-backup scheme on top of a per-data-center atomic algorithm that broadcasts messages within a single data center. This combination presents some unique challenges, such as handling the simultaneous occurrence of failures and disasters, and preventing the plurality of processes within a single data center from resulting in a plurality of messages being communicated between data centers.

Language context effects on interlingual homograph recognition: evidence from event-related potentials and response times in semantic priming

Dutch–English bilinguals performed a generalized lexical decision task on triplets of items, responding with “yes” if all three items were correct Dutch and/or English words, and with “no” if one or more of the items was not a word in either language. Sometimes the second item in a triplet was an interlingual homograph whose English meaning was semantically related to the third item of the triplet (e.g., HOUSE – ANGEL – HEAVEN, where ANGEL means “sting” in Dutch). In such cases, the first item was either an exclusively English (HOUSE) or an exclusively Dutch (ZAAK) word. Semantic priming effects were found in on-line response times. Event-related potentials that were recorded simultaneously showed N400 priming effects thought to reflect semantic integration processes. The response time and N400 priming effects were not affected by the language of the first item in the triplets, providing evidence in support of a strong bottom-up role with respect to bilingual word recognition. The results are interpreted in terms of the Bilingual Interactive Activation model, a language nonselective access model assuming bottom-up priority.

The counting stroop: An interference task specialized for functional neuroimaging-validation study with functional MRI

The anterior cingulate cortex has been activated by color Stroop tasks, supporting the hypothesis that it is recruited to mediate response selection or allocate attentional resources when confronted with competing information-processing streams. The current study used the newly developed "Counting Stroop" to identify the mediating neural substrate of cognitive interference. The Counting Stroop, a Stroop variant allowing on-line response time measurements while obviating speech, was created because speaking produces head movements that can exceed those tolerated by functional magnetic resonance imaging (fMRI), preventing the collection of vital performance data. During this task, subjects report by button-press the number of words (1-4) on the screen, regardless of word meaning. Interference trials contain number words that are incongruent with the correct response (e.g., "two" written three times), while neutral trials contain single semantic category common animals (e.g., "bird"). Nine normal right-handed adult volunteers underwent fMRI while performing the Counting Stroop. Group fMRI data revealed significant (P < or = 10(-4) activity in the cognitive division of anterior cingulate cortex when contrasting the interference vs. neutral conditions. On-line performance data showed 1) longer reaction times for interference blocks than for neutral ones, and 2) decreasing reaction times with practice during interference trials (diminished interference effects), indicating that learning occurred. The performance data proved to be a useful guide in analyzing the image data. The relative difference in anterior cingulate activity between the interference and neutral conditions decreased as subjects learned the task. These findings have ramifications for attentional, cognitive interference, learning, and motor control mechanism theories.

The effects of different on-line adaptive response time limits on speed and amount of learning in computer assisted instruction and intelligent tutoring

Instructional systems usually do not limit the time available to a learner for responding to questions or practice items. However, experiments conducted by Robert Tennyson and his research group indicate that with regard to the speed of learning this common practice is less efficient compared with the computer-controlled adaptation of a proper response time limit to the learner's increasing competence during instruction. Until now the theoretical background of these results is not well understood and the effects are only reported by a single research group. In this article two experiments are reported. They are based on recent cognitive theories and are aiming at differences between learner control of the response time and adaptive program control of a response time limit on speed and amount of rule learning. Experiment number 1 ( N = 66, 3-group-ANCOVA-design) replicated the results of Tennyson and co-workers: Learning speed is highest under a response time limit which is adapted on-line to the achievement of the student in such a way that there is short time available to respond at low achievement and more time at increasing achievement. Learning speed is slowest under a response time limit which is inversely adapted to increasing achievement. Learner control without any time limit is located in-between. Experiment number 2 ( N = 40, 2-group-ANCOVA-design) extends this effect to the overall level or amount of learning within a fixed time period: Students learn more under an adaptive response time limit than under learner control without any response time limit. This effect, however, depends on a successful implementation of the algorithm to adjust the response time limit. Otherwise there is a kind of boomerang effect by which learning is hindered. Furthermore, the results indicate that the effects of an adaptive response time limit are more cognitive than motivational, so that they are in accordance with modern cognitive theories like ACT∗ and repair theory.